TILM3619 Bayesian Computation (5 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
0-5
Description
- computational methods, in particular Markov Chain Monte Carlo (MCMC)
- one parameter models, multiparameter models, hierarchical models
- Stan software for running MCMC simulations in real problems
- model checking
- model evaluation and comparison
- decision analysis
- asymptotics
The exact contents vary by each implementation of the course.
Learning outcomes
The student can
- formulate a Bayesian model for certain common problems
- apply numerical methods for learning the parameters of a given model
- evaluate the fit of a model for a given problem
- apply Bayesian analysis in certain decision problems
Additional information
Suoritettavissa vuosittain.
Description of prerequisites
- TILM3708 Statistical programming and visualisation
- TILM3709 Bayesian inference
- TILM3618 Introduction to Computational Statistics